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A Research-Teaching Guide for Visual Data Analysis in Digital Humanities

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Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2020)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1474))

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Abstract

The use of visualization to underpin distant reading arguments on cultural heritage data has established in the digital humanities domain. Novel strategies to represent data visually typically arise from interdisciplinary projects involving humanities and visualization scholars. However, the quality of outcomes might be inhibited as typical challenges of interdisciplinary research arise, and, at the same time, problem solving strategies are missing. I taught a course on visual data analysis in the digital humanities to let students with diverse study backgrounds experience those challenges in their early academic careers. This paper illustrates the research-teaching components of my course. This includes the contents of the theoretical training with active learning tasks, aspects of the practical training and considerations for teachers aiming to compose a related course.

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Notes

  1. 1.

    https://books.google.com/ngrams.

  2. 2.

    https://datastudio.withgoogle.com/.

  3. 3.

    https://leafletjs.com/.

  4. 4.

    http://www.informatik.uni-leipzig.de/geotemco/.

  5. 5.

    http://timeline.knightlab.com/.

  6. 6.

    https://www.sutori.com/.

  7. 7.

    https://gephi.org/.

  8. 8.

    https://hdlab.stanford.edu/palladio/.

  9. 9.

    https://voyant-tools.org/.

  10. 10.

    http://tapor.ca/.

  11. 11.

    https://www.hi.uni-stuttgart.de/gnt/pdm/.

  12. 12.

    https://home.uni-leipzig.de/mim/musici/.

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Author information

Authors and Affiliations

  1. IMADA, University of Southern Denmark, Odense, Denmark

    Stefan Jänicke

Authors
  1. Stefan Jänicke
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Correspondence to Stefan Jänicke .

Editor information

Editors and Affiliations

  1. IRISA, University of Rennes 1, Rennes, France

    Kadi Bouatouch

  2. Universidade do Porto, Porto, Portugal

    A. Augusto de Sousa

  3. University of Genova, Genova, Italy

    Manuela Chessa

  4. Mines ParisTech, Paris, France

    Alexis Paljic

  5. Linnaeus University, Växjö, Sweden

    Andreas Kerren

  6. French Civil Aviation University (ENAC), Toulouse, France

    Christophe Hurter

  7. Università di Catania, Catania, Italy

    Giovanni Maria Farinella

  8. Universitat de Barcelona, Barcelona, Spain

    Petia Radeva

  9. Escola Superior de Tecnologia de Setúbal, Setúbal, Portugal

    Jose Braz

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Jänicke, S. (2022). A Research-Teaching Guide for Visual Data Analysis in Digital Humanities. In: Bouatouch, K., et al. Computer Vision, Imaging and Computer Graphics Theory and Applications. VISIGRAPP 2020. Communications in Computer and Information Science, vol 1474. Springer, Cham. https://doi.org/10.1007/978-3-030-94893-1_9

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